Abstract
Abstract Interim analysis of accumulating data in a clinical trial is now an established practice for ethical and scientific reasons. Repeatedly testing interim data can inflate false positive error rates if not handled appropriately. Group sequential methods are a commonly used frequentist approach to control this error rate. Motivated by experience of clinical trials, the alpha spending function is one way to implement group sequential boundaries that control the type I error rate while allowing flexibility in how many interim analyses are to be conducted and at what times. In this paper, we review the alpha spending function approach, and detail its applicability to a variety of commonly used statistical procedures, including survival and longitudinal methods.
Keywords
InterimFrequentist inferenceInterim analysisFlexibility (engineering)Type I and type II errorsComputer scienceFunction (biology)EconometricsStatisticsClinical trialMedicineMathematicsBayesian probabilityBayesian inference
MeSH Terms
BiasClinical Trials as TopicData InterpretationStatisticalDouble-Blind MethodHumansLongitudinal StudiesMulticenter Studies as TopicMyocardial InfarctionPropranololRandomized Controlled Trials as TopicSurvival Analysis
Affiliated Institutions
Related Publications
A Direct Approach to False Discovery Rates
Summary Multiple-hypothesis testing involves guarding against much more complicated errors than single-hypothesis testing. Whereas we typically control the type I error rate for...
Multiple Hypotheses Testing with Weights
In this paper we offer a multiplicity of approaches and procedures for multiple testing problems with weights. Some rationale for incorporating weights in multiple hypotheses te...
Semiparametric Regression for the Mean and Rate Functions of Recurrent Events
Summary The counting process with the Cox-type intensity function has been commonly used to analyse recurrent event data. This model essentially assumes that the underlying coun...
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
SUMMARY The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A diff...
Multiple testing in clinical trials
Abstract The basic ideas of multiple testing are outlined and the problem of how to control the probability of erroneous decisions is discussed. The main emphasis is on the conc...
Publication Info
- Year
- 1994
- Type
- article
- Volume
- 13
- Issue
- 13-14
- Pages
- 1341-1352
- Citations
- 547
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
547
OpenAlex
20
Influential
436
CrossRef
Cite This
David L. DeMets,
K. K. Gordon Lan
(1994).
Interim analysis: The alpha spending function approach.
Statistics in Medicine
, 13
(13-14)
, 1341-1352.
https://doi.org/10.1002/sim.4780131308
Identifiers
- DOI
- 10.1002/sim.4780131308
- PMID
- 7973215